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Journal articles on the topic 'Moments Models'

Author: Grafiati

Published: 25 January 2025

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1

Hunana, P., T. Passot, E. Khomenko, D. Martínez-Gómez, M. Collados, A. Tenerani, G. P. Zank, Y. Maneva, M. L. Goldstein, and G. M. Webb. "Generalized Fluid Models of the Braginskii Type." Astrophysical Journal Supplement Series 260, no. 2 (June 1, 2022): 26. http://dx.doi.org/10.3847/1538-4365/ac5044.

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Abstract Several generalizations of the well-known fluid model of Braginskii (1965) are considered. We use the Landau collisional operator and the moment method of Grad. We focus on the 21-moment model that is analogous to the Braginskii model, and we also consider a 22-moment model. Both models are formulated for general multispecies plasmas with arbitrary masses and temperatures, where all of the fluid moments are described by their evolution equations. The 21-moment model contains two “heat flux vectors” (third- and fifth-order moments) and two “viscosity tensors” (second- and fourth-order moments). The Braginskii model is then obtained as a particular case of a one ion–electron plasma with similar temperatures, with decoupled heat fluxes and viscosity tensors expressed in a quasistatic approximation. We provide all of the numerical values of the Braginskii model in a fully analytic form (together with the fourth- and fifth-order moments). For multispecies plasmas, the model makes the calculation of the transport coefficients straightforward. Formulation in fluid moments (instead of Hermite moments) is also suitable for implementation into existing numerical codes. It is emphasized that it is the quasistatic approximation that makes some Braginskii coefficients divergent in a weakly collisional regime. Importantly, we show that the heat fluxes and viscosity tensors are coupled even in the linear approximation, and that the fully contracted (scalar) perturbations of the fourth-order moment, which are accounted for in the 22-moment model, modify the energy exchange rates. We also provide several appendices, which can be useful as a guide for deriving the Braginskii model with the moment method of Grad.

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2

Hu, Zhicheng, Ruo Li, and Zhonghua Qiao. "Extended Hydrodynamic Models and Multigrid Solver of a Silicon Diode Simulation." Communications in Computational Physics 20, no. 3 (August 31, 2016): 551–82. http://dx.doi.org/10.4208/cicp.290615.020316a.

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AbstractExtended hydrodynamic models for carrier transport are derived from the semiconductor Boltzmann equation with relaxation time approximation of the scattering term, by using the globally hyperbolic moment method and the moment-dependent relaxation time. Incorporating the microscopic relaxation time and the applied voltage bias, a formula is proposed to determine the relaxation time for each moment equation, which sets different relaxation rates for different moments such that higher moments damp faster. The resulting models would give more satisfactory results of macroscopic quantities of interest with a high-order convergence to those of the underlying Boltzmann equation as the involved moments increase, in comparison to the corresponding moment models using a single relaxation time. In order to simulate the steady states efficiently, a multigrid solver is developed for the derived moment models. Numerical simulations of an n+-n-n+ silicon diode are carried out to demonstrate the validation of the presented moment models, and the robustness and efficiency of the designed multigrid solver.

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3

Xiao, Zhiguo. "The weighted method of moments approach for moment condition models." Economics Letters 107, no. 2 (May 2010): 183–86. http://dx.doi.org/10.1016/j.econlet.2010.01.019.

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4

Hu, Yi, Xiaohua Xia, Ying Deng, and Dongmei Guo. "Higher Order Mean Squared Error of Generalized Method of Moments Estimators for Nonlinear Models." Discrete Dynamics in Nature and Society 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/324904.

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Generalized method of moments (GMM) has been widely applied for estimation of nonlinear models in economics and finance. Although generalized method of moments has good asymptotic properties under fairly moderate regularity conditions, its finite sample performance is not very well. In order to improve the finite sample performance of generalized method of moments estimators, this paper studies higher-order mean squared error of two-step efficient generalized method of moments estimators for nonlinear models. Specially, we consider a general nonlinear regression model with endogeneity and derive the higher-order asymptotic mean square error for two-step efficient generalized method of moments estimator for this model using iterative techniques and higher-order asymptotic theories. Our theoretical results allow the number of moments to grow with sample size, and are suitable for general moment restriction models, which contains conditional moment restriction models as special cases. The higher-order mean square error can be used to compare different estimators and to construct the selection criteria for improving estimator’s finite sample performance.

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5

Petričková, Anna. "Moments of Markov-Switching Models." Tatra Mountains Mathematical Publications 61, no. 1 (December 1, 2014): 131–40. http://dx.doi.org/10.2478/tmmp-2014-0032.

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Abstract In this paper we have focused on the class of regime-switching time series models with regimes determined by unobservable variables, concretely Markov-switching models. We have derived 2nd central moment of the MSW models for two cases-state-independent and state-dependent model

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6

Peck, Jamie, Nik Theodore, and Neil Brenner. "Neoliberal Urbanism: Models, Moments, Mutations." SAIS Review of International Affairs 29, no. 1 (2009): 49–66. http://dx.doi.org/10.1353/sais.0.0028.

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7

Amendola, Alessandra, Marcella Niglio, and Cosimo Vitale. "The moments of SETARMA models." Statistics & Probability Letters 76, no. 6 (March 2006): 625–33. http://dx.doi.org/10.1016/j.spl.2005.09.016.

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8

Timmermann, Allan. "Moments of Markov switching models." Journal of Econometrics 96, no. 1 (May 2000): 75–111. http://dx.doi.org/10.1016/s0304-4076(99)00051-2.

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9

Brekke, L. "Baryon Magnetic Moments in Quark Models with Anomalous Quark Moments." Annals of Physics 240, no. 2 (June 1995): 400–431. http://dx.doi.org/10.1006/aphy.1995.1050.

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10

Gasparutto, Xavier, Eric Jacquelin, and Raphael Dumas. "Contribution of passive actions to the lower limb joint moments and powers during gait: A comparison of models." Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine 232, no. 8 (July 13, 2018): 768–78. http://dx.doi.org/10.1177/0954411918785661.

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The lower limb passive actions representing the actions of all the passive periarticular structures have been shown to have a significant contribution to the power generation and absorption during gait. However, the respective magnitude of its different components was not established, although models of ligament moment were implemented in some musculoskeletal models. These ligament moments have shown to have an influence on the musculo-tendon forces and contact forces but the models used were never specifically evaluated, that is, compared to the passive and net joint moments. Two models of passive joint moments and three models of ligament moments were selected from the literature. Ten subjects (23–29 years old, 79.8 ± 9.5 kg, 1.85 ± 0.06 m) participated in the study. Each subject performed three gait cycles in a gait laboratory to acquire the kinematics and ground reaction forces and to compute the ligament, passive and net moments of the right lower limb joints. The contributions of the passive joint moments to the net joint moments were in accordance with the literature, although time shifts appeared for peaks in the hip and knee powers. Two of the models of ligament moments seemed, in fact, to represent the passive joint moments as their contributions were very similar while the third model of ligament moments seemed to represent only penalty-based joint limits. As a conclusion, this study showed that the models of ligament moments existing in the literature do not seem reliable. This study also demonstrated that the use of non-subject-specific models of the passive joint moments could be a valid approach for healthy subjects.

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11

Chen, Ming-Hua, and Zuu-Chang Hong. "A pdf Description of Turbulent Axisymmetric Free Jet Flow." Journal of Fluids Engineering 121, no. 1 (March 1, 1999): 73–79. http://dx.doi.org/10.1115/1.2822015.

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This study presents the applications of a turbulence probability density function (pdf) equation to compute an axisymmetric turbulent free jet flow. In view of the difficulty of solving this pdf equation directly by conventional numerical methods, an approximate moment method is applied. The Calculated triple velocity correlations appearing in the second-order moments equation are calculated and compared with measured values and with those estimated by moment-closure models. The results reveal that the pdf approach gives consistency in the higher-order moments and radial budget of third moments of velocity, and that the neglect of the mean-strain production, the rapid part of the pressure correlation and the dissipation are responsible for deviations between moment-closure models and experiments. Therefore, pdf methods appear to be more suitable than conventional moment-closure models in terms of revealing turbulence structure.

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12

Stirling, A. J., and J. A. Peacock. "Non-Gaussian Isocurvature Models." Symposium - International Astronomical Union 183 (1999): 268. http://dx.doi.org/10.1017/s0074180900132851.

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Peebles (1997) has proposed a non-Gaussian χ2isocurvature model which gives rise to early galaxy assembly at redshifts ≥ 3–4. We test whether the higher order moments (skewness and kurtosis) of such a model are compatible with the moments of the observed density field, and find that in the absence of bias these models produce moments that are much higher than those measured for the APM survey (Gaztañaga, 1994). We have applied different biasing schemes to see whether bias can bring the moments down, and find that for power law, Cen-Ostriker, and censor threshold biasing schemes (Mann et al 1997) the moments can be brought into agreement with the APM measurements only for linear bias valuesb> 3. This however, would give a redshift distortion parameter, βopticai= (Ω0.6/b) < 0.16 which is inconsistent with current estimates from redshift surveys of βoptical= 0.40 ± 0.12 (e.g. Peacock 1997). We conclude that for an acceptable level of bias in the schemes we have tested, the χ2isocurvature model moments disagree with current measurements of skewness and kurtosis from the APM survey.

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13

Mat Jan, Nur Amalina, Ani Shabri, and Ruhaidah Samsudin. "Handling non-stationary flood frequency analysis using TL-moments approach for estimation parameter." Journal of Water and Climate Change 11, no. 4 (August 16, 2019): 966–79. http://dx.doi.org/10.2166/wcc.2019.055.

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Abstract Non-stationary flood frequency analysis (NFFA) plays an important role in addressing the issue of the stationary assumption (independent and identically distributed flood series) that is no longer valid in infrastructure-designed methods. This confirms the necessity of developing new statistical models in order to identify the change of probability functions over time and obtain a consistent flood estimation method in NFFA. The method of Trimmed L-moments (TL-moments) with time covariate is confronted with the L-moment method for the stationary and non-stationary generalized extreme value (GEV) models. The aims of the study are to investigate the behavior of the proposed TL-moments method in the presence of NFFA and applying the method along with GEV distribution. Comparisons of the methods are made by Monte Carlo simulations and bootstrap-based method. The simulation study showed the better performance of most levels of TL-moments method, which is TL(η,0), (η = 2, 3, 4) than the L-moment method for all models (GEV1, GEV2, and GEV3). The TL-moment method provides more efficient quantile estimates than other methods in flood quantiles estimated at higher return periods. Thus, the TL-moments method can produce better estimation results since the L-moment eliminates lowest value and gives more weight to the largest value which provides important information.

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14

Dedík, L., and M. Ďurišová. "General Moments in Linear Pharmacokinetic Models." Clinical Research and Regulatory Affairs 13, no. 3-4 (January 1996): 199–210. http://dx.doi.org/10.3109/10601339609035952.

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15

Bentarzi, M., and M. Merzougui. "Moments of Mixture Periodic Autoregressive Models." Communications in Statistics - Theory and Methods 40, no. 22 (November 15, 2011): 3937–47. http://dx.doi.org/10.1080/03610926.2010.503017.

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16

Wu, Ping, Yun Fang, and Li-Xing Zhu. "Estimating Moments in Linear Mixed Models." Communications in Statistics - Theory and Methods 37, no. 16 (June 25, 2008): 2582–94. http://dx.doi.org/10.1080/03610920801947644.

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17

Chan, April S., Helen H. N. Yan, and Suet Yi Leung. "Breakthrough Moments: Organoid Models of Cancer." Cell Stem Cell 24, no. 6 (June 2019): 839–40. http://dx.doi.org/10.1016/j.stem.2019.05.006.

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18

Bosdogianni, P., M. Petrou, and J. Kittler. "Mixture models with higher order moments." IEEE Transactions on Geoscience and Remote Sensing 35, no. 2 (March 1997): 341–53. http://dx.doi.org/10.1109/36.563273.

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19

Huang, Zhiyue, and Paul Marriott. "Parameterizing mixture models with generalized moments." Annals of the Institute of Statistical Mathematics 68, no. 2 (October 15, 2014): 269–97. http://dx.doi.org/10.1007/s10463-014-0490-9.

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20

Kryvyi, O. F., M. V. Miyusov, and M. O. Kryvyi. "MATHEMATICAL MODELING OF THE OPERATION OF SHIP'S PROPELLERS WITH DIFFERENT MANEUVERING MODES." Shipping & Navigation 32, no. 2 (December 12, 2021): 71–87. http://dx.doi.org/10.31653/2306-5761.32.2021.71-87.

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In the study of ship maneuvers, in the development of ship's autopilots and simulators, the availability of adequate mathematical models of the ship’s propulsion complex, which would describe with high accuracy the dynamics of the ship for the widest ranges of phase coordinates, plays a decisive role. Mathematical models of ship dynamics consist of mathematical models of inertial and non-inertial forces and moments on the ship's hull. The latter include hydrodynamic and aerodynamic forces and moments on the ship's hull, forces and moments caused by the operation of propellers, rigging, ship rudders. For the adequacy of the general mathematical model of the ship's dynamics, the adequacy of the mathematical models of all components of non-inertial forces and moments on the ship's hull is necessary. Mathematical models of non-inertial forces and moments on a ship's hull are usually empirical and made by processing data from experimental tests in ship model basin or in full-scale sea trials. In particular, this applies to the forces and moments caused by the operation of the propeller. In the mathematical modeling of the indicated forces and moments, the rectilinear movement of the vessel, or movement at small values of the drift angles, is usually considered. In this case, only the longitudinal action of the propeller is usually considered, and the transverse component of the force and the moment on the ship's propeller are unreasonably neglected. In addition, well-known mathematical models usually contain coefficients and functions that are difficult to determine using tables and graphs, which is inconvenient for numerical modeling. This work is intended to somewhat eliminate the indicated disadvantages. In particular, it was investigated how the curvilinear movement of the ship affects the operation of the propeller, analyzed the existing mathematical models, and new effective mathematical models of the longitudinal and transverse components of the force and moment caused by the operation of the ship's propeller in dimensional and dimensionless forms were proposed. In particular, representations are obtained for the dimensionless coefficients of the propeller stop and the moment on the propeller shaft, the wake fraction coefficient, the thrust-deduction factor, and skew of the flow on the propeller. It is shown how these parameters change for all possible values of the drift angle and angular velocity. For a number of commercial vessels of various types, technical characteristics are given, and parameters for constructing mathematical models of the dynamics of the propeller are calculated.

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21

Kurdyaeva, Tamara, and Andreas Milias-Argeitis. "Uncertainty propagation for deterministic models of biochemical networks using moment equations and the extended Kalman filter." Journal of The Royal Society Interface 18, no. 181 (August 2021): 20210331. http://dx.doi.org/10.1098/rsif.2021.0331.

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Differential equation models of biochemical networks are frequently associated with a large degree of uncertainty in parameters and/or initial conditions. However, estimating the impact of this uncertainty on model predictions via Monte Carlo simulation is computationally demanding. A more efficient approach could be to track a system of low-order statistical moments of the state. Unfortunately, when the underlying model is nonlinear, the system of moment equations is infinite-dimensional and cannot be solved without a moment closure approximation which may introduce bias in the moment dynamics. Here, we present a new method to study the time evolution of the desired moments for nonlinear systems with polynomial rate laws. Our approach is based on solving a system of low-order moment equations by substituting the higher-order moments with Monte Carlo-based estimates from a small number of simulations, and using an extended Kalman filter to counteract Monte Carlo noise. Our algorithm provides more accurate and robust results compared to traditional Monte Carlo and moment closure techniques, and we expect that it will be widely useful for the quantification of uncertainty in biochemical model predictions.

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22

Kytölä, Ulla, and Anssi Laaksonen. "Prediction of Restraint Moments in Precast, Prestressed Structures Made Continuous." Nordic Concrete Research 59, no. 1 (December 1, 2018): 73–93. http://dx.doi.org/10.2478/ncr-2018-0016.

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Abstract This paper studies restraint moments developing in simple-span precast, prestressed beams made continuous. Methods of evaluating restraint moments produced by creep and differential shrinkage are presented. Shrinkage and creep properties of composite structures, beam and deck parts were tested and compared to values defined according to Eurocode models. Finally, the restraint moments were calculated with both material models for the two-span parking deck structure. The study confirmed the findings of previous studies: that the methods that are used overestimate the negative restraint moment produced by differential shrinkage.

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23

Kuba, Markus, and Alois Panholzer. "Limiting Distributions for a Class Of Diminishing Urn Models." Advances in Applied Probability 44, no. 1 (March 2012): 87–116. http://dx.doi.org/10.1239/aap/1331216646.

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In this work we analyze a class of 2 × 2 Pólya-Eggenberger urn models with ball replacement matrix and c = pa with . We determine limiting distributions by obtaining a precise recursive description of the moments of the considered random variables, which allows us to deduce asymptotic expansions of the moments. In particular, we obtain limiting distributions for the pills problem a = c = d = 1, originally proposed by Knuth and McCarthy. Furthermore, we also obtain limiting distributions for the well-known sampling without replacement urn, a = d = 1 and c = 0, and generalizations of it to arbitrary and c = 0. Moreover, we obtain a recursive description of the moment sequence for a generalized problem.

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24

Kuba, Markus, and Alois Panholzer. "Limiting Distributions for a Class Of Diminishing Urn Models." Advances in Applied Probability 44, no. 01 (March 2012): 87–116. http://dx.doi.org/10.1017/s0001867800005462.

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In this work we analyze a class of 2 × 2 Pólya-Eggenberger urn models with ball replacement matrix and c = pa with . We determine limiting distributions by obtaining a precise recursive description of the moments of the considered random variables, which allows us to deduce asymptotic expansions of the moments. In particular, we obtain limiting distributions for the pills problem a = c = d = 1, originally proposed by Knuth and McCarthy. Furthermore, we also obtain limiting distributions for the well-known sampling without replacement urn, a = d = 1 and c = 0, and generalizations of it to arbitrary and c = 0. Moreover, we obtain a recursive description of the moment sequence for a generalized problem.

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25

Morrison, Hugh, Matthew R. Kumjian, Charlotte P. Martinkus, Olivier P. Prat, and Marcus van Lier-Walqui. "A General N-Moment Normalization Method for Deriving Raindrop Size Distribution Scaling Relationships." Journal of Applied Meteorology and Climatology 58, no. 2 (February 2019): 247–67. http://dx.doi.org/10.1175/jamc-d-18-0060.1.

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AbstractA general drop size distribution (DSD) normalization method is formulated in terms of generalized power series relating any DSD moment to any number and combination of reference moments. This provides a consistent framework for comparing the variability of normalized DSD moments using different sets of reference moments, with no explicit assumptions about the DSD functional form (e.g., gamma). It also provides a method to derive any unknown moment plus an estimate of its uncertainty from one or more known moments, which is relevant to remote sensing retrievals and bulk microphysics schemes in weather and climate models. The approach is applied to a large dataset of disdrometer-observed and bin microphysics-modeled DSDs. As expected, the spread of normalized moments decreases as the number of reference moments is increased, quantified by the logarithmic standard deviation of the normalized moments, σ. Averaging σ for all combinations of reference moments and normalized moments of integer order 0–10, 42.9%, 81.3%, 93.7%, and 96.9% of spread are accounted for applying one-, two-, three-, and four-moment normalizations, respectively. Thus, DSDs can be well characterized overall using three reference moments, whereas adding a fourth reference moment contributes little independent information. The spread of disdrometer-observed DSD moments from uncertainty associated with drop count statistics generally lies between values of σ using two- and three-moment normalizations. However, this uncertainty has little impact on the derived DSD scaling relationships or σ when considered.

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26

Nghiem, Linh H., Michael C. Byrd, and Cornelis J. Potgieter. "Estimation in linear errors-in-variables models with unknown error distribution." Biometrika 107, no. 4 (May 21, 2020): 841–56. http://dx.doi.org/10.1093/biomet/asaa025.

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Summary Parameter estimation in linear errors-in-variables models typically requires that the measurement error distribution be known or estimable from replicate data. A generalized method of moments approach can be used to estimate model parameters in the absence of knowledge of the error distributions, but it requires the existence of a large number of model moments. In this paper, parameter estimation based on the phase function, a normalized version of the characteristic function, is considered. This approach requires the model covariates to have asymmetric distributions, while the error distributions are symmetric. Parameters are estimated by minimizing a distance function between the empirical phase functions of the noisy covariates and the outcome variable. No knowledge of the measurement error distribution is needed to calculate this estimator. Both asymptotic and finite-sample properties of the estimator are studied. The connection between the phase function approach and method of moments is also discussed. The estimation of standard errors is considered and a modified bootstrap algorithm for fast computation is proposed. The newly proposed estimator is competitive with the generalized method of moments, despite making fewer model assumptions about the moment structure of the measurement error. Finally, the proposed method is applied to a real dataset containing measurements of air pollution levels.

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27

Winterstein, S. R., and C. H. Lange. "Load Models for Fatigue Reliability From Limited Data." Journal of Solar Energy Engineering 118, no. 1 (February 1, 1996): 64–68. http://dx.doi.org/10.1115/1.2847953.

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Probability distributions of wind turbine loads are estimated from limited data. The impact of different models on fatigue damage is shown. Common one-parameter probability models, such as the Rayleigh and exponential, are found to give significantly different estimates of load distributions and damage. Greatest differences occur in materials with relatively high values of the S–N exponent b, such as composites. In such cases more accurate damage estimates are found by matching at least two moments of the load data (Weibull model), or still higher moments as well. For this purpose, a new, four-moment “generalized Weibull” model is introduced. For edgewise loads it appears a notable improvement over the basic Weibull model, while it supports the Weibull model in the flapwise case. Uncertainty in damage estimates is also quantified, along with the implied data needs.

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28

Wang, Zhi Yun, and Shou Ju Li. "Analytical Computational Models for Relationship between Ultimate Bending Moment of Concrete Segments and Axial Force." Key Engineering Materials 853 (July 2020): 177–81. http://dx.doi.org/10.4028/www.scientific.net/kem.853.177.

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Concrete segments are widely used to support soil and water loadings in shield-excavated tunnels. Concrete segments burden simultaneously to the loadings of bending moments and axial forces. Based on plane deformation assumption of material mechanics, in which plane section before bending remains plane after bending, ultimate bending moment model is proposed to compute ultimate bearing capacity of concrete segments. Ultimate bending moments of concrete segments computed by analytical models agree well with numerical simulation results by FEM. The accuracy of proposed analytical computational model for ultimate bending moment of concrete segments is numerically verified. The analytical computational model and numerical simulation for a practical engineering case indicate that the ultimate bending moment of concrete segments increases with increase of axial force on concrete segment in the case of large eccentricity compressive state.

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29

Lynth, Thomas B., Timothy A. Max, Harold E. Burkhart, and Jiping Liu. "Prediction Equations for Centers of Gravity and Moments of Inertia of Loblolly Pine Stems." Forest Science 39, no. 2 (May 1, 1993): 260–74. http://dx.doi.org/10.1093/forestscience/39.2.260.

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Abstract Adequate design of tree harvesting equipment requires reliable estimates of centers of gravity and moments of inertia for full trees and tree-length stems. Several prediction models were developed for both centers of gravity and moments of inertia based on the theory of geometric solids. These models were fitted to center of gravity and moment of inertia estimates that were derived from stem dimension and weight measurements on loblolly pine (Pinus taeda L.) trees. The models were compared, and the best prediction equations for center of gravity and moment of inertia of tree-length stems were identified. Application of standard multiple regression methods resulted in a moment of inertia prediction model with a slope parameter estimate that had a sign opposite to that indicated by a theoretical model. Ridge regression and nonlinear regression were used to fit moment of inertia prediction models having coefficient signs consistent with those predicted by the theoretical model. The parameter estimates obtained by nonlinear regression were selected since they conformed more closely to properties of the theoretical moment of inertia model. FOR. SCI 39(2):260-274.

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30

Anghelache Nastase, Iulia-Nela, Simona Moldovanu, and Luminita Moraru. "Image Moment-Based Features for Mass Detection in Breast US Images via Machine Learning and Neural Network Classification Models." Inventions 7, no. 2 (June 15, 2022): 42. http://dx.doi.org/10.3390/inventions7020042.

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Differentiating between malignant and benign masses using machine learning in the recognition of breast ultrasound (BUS) images is a technique with good accuracy and precision, which helps doctors make a correct diagnosis. The method proposed in this paper integrates Hu’s moments in the analysis of the breast tumor. The extracted features feed a k-nearest neighbor (k-NN) classifier and a radial basis function neural network (RBFNN) to classify breast tumors into benign and malignant. The raw images and the tumor masks provided as ground-truth images belong to the public digital BUS images database. Certain metrics such as accuracy, sensitivity, precision, and F1-score were used to evaluate the segmentation results and to select Hu’s moments showing the best capacity to discriminate between malignant and benign breast tissues in BUS images. Regarding the selection of Hu’s moments, the k-NN classifier reached 85% accuracy for moment M1 and 80% for moment M5 whilst RBFNN reached an accuracy of 76% for M1. The proposed method might be used to assist the clinical diagnosis of breast cancer identification by providing a good combination between segmentation and Hu’s moments.

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31

Dunne, Adrian. "Statistical Moments in Pharmacokinetics: Models and Assumptions." Journal of Pharmacy and Pharmacology 45, no. 10 (October 1993): 871–75. http://dx.doi.org/10.1111/j.2042-7158.1993.tb05611.x.

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32

Appelquist, Thomas, Maurizio Piai, and Robert Shrock. "Lepton dipole moments in extended technicolor models." Physics Letters B 593, no. 1-4 (July 2004): 175–80. http://dx.doi.org/10.1016/j.physletb.2004.04.062.

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33

Juliá-Dı́az, B., and D. O. Riska. "Baryon magnetic moments in relativistic quark models." Nuclear Physics A 739, no. 1-2 (July 2004): 69–88. http://dx.doi.org/10.1016/j.nuclphysa.2004.03.078.

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34

Jakubowski, Jacek, and Jerzy Zabczyk. "Exponential moments for HJM models with jumps." Finance and Stochastics 11, no. 3 (April 18, 2007): 429–45. http://dx.doi.org/10.1007/s00780-007-0040-x.

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35

Li, Zaixing, Fei Chen, and Lixing Zhu. "Estimating moments in ANOVA-type mixed models." Metrika 80, no. 6-8 (August 2, 2017): 697–715. http://dx.doi.org/10.1007/s00184-017-0623-2.

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36

Couture, G., J. N. Ng, J. L. Hewett, and T. G. Rizzo. "Anomalous moments ofWbosons in broken-supersymmetric models." Physical Review D 38, no. 3 (August 1, 1988): 860–64. http://dx.doi.org/10.1103/physrevd.38.860.

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37

Castella, F., G. Dujardin, and B. Sericola. "Moments’ Analysis in Homogeneous Markov Reward Models." Methodology and Computing in Applied Probability 11, no. 4 (May 10, 2008): 583–601. http://dx.doi.org/10.1007/s11009-008-9075-5.

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Issermann, Maikel, and Fi-John Chang. "Uncertainty Analysis of Spatiotemporal Models with Point Estimate Methods (PEMs)—The Case of the ANUGA Hydrodynamic Model." Water 12, no. 1 (January 14, 2020): 229. http://dx.doi.org/10.3390/w12010229.

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Practitioners often neglect the uncertainty inherent to models and their inputs. Point Estimate Methods (PEMs) offer an alternative to the common, but computationally demanding, method for assessing model uncertainty, Monte Carlo (MC) simulation. PEMs rerun the model with representative values of the probability distribution of the uncertain variable. The results can estimate the statistical moments of the output distribution. Hong’s method is the specific PEM implemented here for a case study that simulates water runoff using the ANUGA model for an area in Glasgow, UK. Elevation is the source of uncertainty. Three realizations of the Sequential Gaussian Simulation, which produces the random error fields that can be used as inputs for any spatial model, are scaled according to representative values of the distribution and their weights. The output from a MC simulation is used for validation. A comparison of the first two statistical moments indicates that Hong’s method tends to underestimate the first moment and overestimate the second moment. Model efficiency performance measures validate the usefulness of Hong’s method for the approximation of the first two moments, despite the method suffering from outliers. Estimation was less accurate for higher moments but the moment estimates were sufficient to use the Grams-Charlier Expansion to fit a distribution to them. Regarding probabilistic flood-inundation maps, Hong’s method shows very similar probabilities in the same areas as the MC simulation. However, the former requires just three 11-minute simulation runs, rather than the 500 required for the MC simulation. Hong’s method therefore appears attractive for approximating the uncertainty of spatiotemporal models.

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Heine, Richard, Kurt Manal, and Thomas S. Buchanan. "Using Hill-Type Muscle Models and EMG Data in a Forward Dynamic Analysis of Joint Moment." Journal of Mechanics in Medicine and Biology 03, no. 02 (June 2003): 169–86. http://dx.doi.org/10.1142/s0219519403000727.

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There has been considerable interest in estimating muscle forces and joint moments from EMG signals, but most approaches have not been very successful. This is largely because robust models of muscle activation dynamics, Hill-type muscle contraction dynamics, and musculoskeletal geometry are generally not included. Here we present a model which includes these sub-models and we determine which model parameters are most important. The models abilities to predict joint moments about the human elbow during time-varying isometric tasks were examined. Inputs to the models were EMGs from eight muscles. Joint moment was the output, which was compared with the measured moment. Models varied in complexity, having up to 59 adjustable parameters. It was found that a seven adjustable parameter model could adequately estimate time-varying joint moments without substantial sacrifice in performance. The key parameters that were fit for each subject were two global gain factors, a time delay term, a non-linear EMG-force term, two muscle activation terms, and a term for skewing the length-tension curve with muscle activation. This approach offers advantages over optimization-based methods for estimating individual muscle forces. Most importantly, it accounts for the way muscles are activated, which makes it potentially powerful to evaluate patients with pathologies.

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Agbonaye, Augustine Iyekeoretin, Ebierin Akpoebidimiyen Otuaro, and Osadolor Christopher Izinyon. "COMPARISON OF L-MOMENT AND METHOD OF MOMENTS AS PARAMETER ESTIMATORS FOR IDENTIFICATION AND CHOICE OF THE MOST APPROPRIATE RAINFALL DISTRIBUTION MODELS FOR DESIGN OF HYDRAULIC STRUCTURES." Journal of Civil Engineering, Science and Technology 13, no. 1 (April 22, 2022): 33–48. http://dx.doi.org/10.33736/jcest.4207.2022.

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In rainfall frequency analysis, the choice of a suitable probability distribution and parameter estimation method is critical in forecasting design rainfall values for varying return periods at every location. Previously, some researchers in Nigeria used the method of moments (MoM) while others used the L-moment method (LMM) as parameter estimators. However, a more accurate result is obtainable if both estimators are used and their results are compared and ranked to obtain the most appropriate distribution models for each location This study compared the performance of two forms of parameter estimation, namely the method of moments (MoM) and the L-moment method (LMM). This was aimed at identifying and selecting the best fit probability distribution models among three distribution models for the design of hydraulic structures. These models are Generalized Pareto (GPA), Generalized Extreme Value (GEV), and Gumbel Extreme Value (EVI). Annual rainfall series of ten gauging stations with data from 33-50 years from ten southern States of Nigeria obtained from NIMET were used for Rainfall Frequency Analysis (RFA). At five locations, the best fit probability model was the GPA probability distribution model with L-Moment. EVI and GEV probability distribution models with the method of moments were the most appropriate probability models at two locations each. EVI probability distribution model with the L-moment was the most appropriate probability model at one place. The findings confirmed that no single distribution outperformed all others at all stations. Since no single model is regarded preferable for all practical purposes, the best-fit probability model with parameter estimator at any location is site-specific. Consequently, available models and parameter estimators are filtered based on the situation at hand and the type of data available. The identified best fit models with the most appropriate parameter estimator would be a tool to help decision-makers in sizing hydraulic structures in the area.

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Bebu, Ionut, and Thomas Mathew. "Confidence intervals for limited moments and truncated moments in normal and lognormal models." Statistics & Probability Letters 79, no. 3 (February 2009): 375–80. http://dx.doi.org/10.1016/j.spl.2008.09.006.

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Yee, Albert G., and C. Daniel Mote. "Forces and Moments at the Knee and Boot Top: Models for an Alpine Skiing Population." Journal of Applied Biomechanics 13, no. 3 (August 1997): 373–84. http://dx.doi.org/10.1123/jab.13.3.373.

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The purpose of this study was to identify regression models to predict moments at the boot top and knee from the force components at the bindings for a sample of skiers. Six subjects skied a slalom course, first with their boots set to the least stiff setting and then with their boots set to the most stiff setting. Six load component dynamometers measured force and moment components at the toe and heel bindings. An electrogoniometer measured ankle flexion. Regression models were developed for the subject sample that predicted quasi-static moment components at the boot top and knee from measurements of ankle flexion and the quasi-static force components at the bindings. Large anterior bending moment was not necessarily accompanied by large ankle flexion, which emphasized that binding designs and standards for injury prevention must account for forces and moments at the sites of potential injury, rather than limiting consideration to boot stiffness or forces at the bindings.

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TAMRAZYAN, A. G., and Y. A. K. SAYED. "EXPERIMENTAL STUDY OF THE COEFFICIENT OF MOMENT REDISTRIBUTION IN STATICALLY INDETERMINATE RC BEAMS." Building and reconstruction 109, no. 5 (2023): 24–35. http://dx.doi.org/10.33979/2073-7416-2023-109-5-24-35.

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This article investigates the coefficient of moments redistribution in statically indeterminate RC beams through an experimental and analytical approach. Two-span statically indeterminate RC beams were tested under bending moment. A discussion of the results of the mode of failure, load-deformation, load-strain, and the coefficient of the moments redistribution were conducted. Moreover, the experimental results were compared to the analytical predictions of the related existing models, including the ACI 318-19 and CSA A23.3-19 codes, and others. The results show that the coefficient of moment redistribution is affected by the reinforcement ratio (µs1) and can be accurately predicted by a recent mathematical analysis. The experimental results also reveal that the moment redistribution capacity of the beams exceeds the values predicted by the other existing models.

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Yu, Kaizhi, and Hong Zou. "The Combined Poisson INMA(q) Models for Time Series of Counts." Journal of Applied Mathematics 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/457842.

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A new stationaryqth-order integer-valued moving average process with Poisson innovation is introduced based on decision random vector. Some statistical properties of the process are established. Estimators of the parameters of the process are obtained using the method of moments. Some numerical results of the estimators are presented to assess the performance of moment estimators.

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Nail-Ulloa, Ivan, Sean Gallagher, Rong Huangfu, Dania Bani-Hani, and Nathan Pool. "Validation of a Wireless Sensor System for the Estimation of Cumulative Lumbar Loads in Occupational Settings." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 65, no. 1 (September 2021): 489–94. http://dx.doi.org/10.1177/1071181321651078.

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This study aimed to evaluate the accuracy of 3D L5/S1 moment estimates from a wearable inertial motioncapture system during manual lifting tasks. Reference L5/S1 moments were calculated using inversedynamics bottom-up and top-down laboratory models, based on the data from a measurement systemcomprising optical motion capture and force plates. Nine groups of four subjects performed tasks consistingof lifting and lowering 10 lbs. load with three different heights and asymmetry angles. As a measure ofsystem performance, the root means square errors and absolute peak errors between models werecompared. Also, repeated measures analyses of variance were calculated comparing the means and theabsolute peaks of the estimated moments. The results suggest that most of the estimates obtained from thewireless sensor system are in close correspondence when comparing the means, and more variability isobserved when comparing peak values to other models calculating estimates of L5/S1 moments.

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Winterstein, Steven R., and Tina Kashef. "Moment-Based Load and Response Models With Wind Engineering Applications." Journal of Solar Energy Engineering 122, no. 3 (May 1, 2000): 122–28. http://dx.doi.org/10.1115/1.1288028.

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A general method is shown here to model wind loads and responses for reliability applications. This method characterizes the short-term loads and responses by a few summary statistics: specifically, by a limited number of statistical moments. A suite of moment-based models are derived and applied here, illustrating how this statistical moment information can best be utilized. Two examples are shown: the fatigue analysis of a wind turbine component, and the vibration response of a fixed structure to nonlinear wind drag loads. [S0199-6231(00)00702-4]

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Armstrong, Timothy B., and Michal Kolesár. "Sensitivity analysis using approximate moment condition models." Quantitative Economics 12, no. 1 (2021): 77–108. http://dx.doi.org/10.3982/qe1609.

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We consider inference in models defined by approximate moment conditions. We show that near‐optimal confidence intervals (CIs) can be formed by taking a generalized method of moments (GMM) estimator, and adding and subtracting the standard error times a critical value that takes into account the potential bias from misspecification of the moment conditions. In order to optimize performance under potential misspecification, the weighting matrix for this GMM estimator takes into account this potential bias and, therefore, differs from the one that is optimal under correct specification. To formally show the near‐optimality of these CIs, we develop asymptotic efficiency bounds for inference in the locally misspecified GMM setting. These bounds may be of independent interest, due to their implications for the possibility of using moment selection procedures when conducting inference in moment condition models. We apply our methods in an empirical application to automobile demand, and show that adjusting the weighting matrix can shrink the CIs by a factor of 3 or more.

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Armstrong, Timothy B., and Michal Kolesár. "Sensitivity analysis using approximate moment condition models." Quantitative Economics 12, no. 1 (2021): 77–108. http://dx.doi.org/10.3982/qe1609.

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We consider inference in models defined by approximate moment conditions. We show that near‐optimal confidence intervals (CIs) can be formed by taking a generalized method of moments (GMM) estimator, and adding and subtracting the standard error times a critical value that takes into account the potential bias from misspecification of the moment conditions. In order to optimize performance under potential misspecification, the weighting matrix for this GMM estimator takes into account this potential bias and, therefore, differs from the one that is optimal under correct specification. To formally show the near‐optimality of these CIs, we develop asymptotic efficiency bounds for inference in the locally misspecified GMM setting. These bounds may be of independent interest, due to their implications for the possibility of using moment selection procedures when conducting inference in moment condition models. We apply our methods in an empirical application to automobile demand, and show that adjusting the weighting matrix can shrink the CIs by a factor of 3 or more.

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Pedersen, Rasmus Søndergaard. "TARGETING ESTIMATION OF CCC-GARCH MODELS WITH INFINITE FOURTH MOMENTS." Econometric Theory 32, no. 2 (September 7, 2015): 498–531. http://dx.doi.org/10.1017/s0266466615000316.

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As an alternative to quasi-maximum likelihood, targeting estimation is a much applied estimation method for univariate and multivariate GARCH models. In terms of variance targeting estimation, recent research has pointed out that at least finite fourth moments of the data generating process is required, if one wants to perform inference in GARCH models by relying on asymptotic normality of the estimator. Such moment conditions may not be satisfied in practice for financial returns, highlighting a potential drawback of variance targeting estimation. In this paper, we consider the large-sample properties of the variance targeting estimator for the multivariate extended constant conditional correlation GARCH model when the distribution of the data generating process has infinite fourth moments. Using nonstandard limit theory, we derive new results for the estimator stating that, under suitable conditions, its limiting distribution is multivariate stable. The rate of consistency of the estimator is slower than$\sqrt T$and depends on the tail shape of the data generating process. A simulation study illustrates the derived properties of the targeting estimator.

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Albert, Wayne J., Joan M. Stevenson, Geneviève A. Dumas, and Roger W. Wheeler. "Effects of shoulder translation on lumbar moment for two dimensional modeling strategies during lifting." Occupational Ergonomics 1, no. 3 (August 1, 1998): 173–87. http://dx.doi.org/10.3233/oer-1998-1302.

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The objectives of this study were to: 1) develop a dynamic 2D link segment model for lifting using the constraints of four sensors from an electromagnetic motion analysis system; 2) evaluate the magnitude of shoulder movement in the sagittal plane during lifting; and 3) investigate the effect of shoulder translation on trunk acceleration and lumbar moments calculated by the developed model and comparing it with two separate 2D dynamic link segment models. Six women and six men lifted loads of 2 kg, 7 kg, 12 kg and 2 kg, 12 kg, 22 kg respectively, under stoop, squat and freestyle conditions. Trunk orientation and position, as well as shoulder position were monitored during all lifts using the Polhemus FASTRAK\trdmk. Results indicated that average range of motion was 0.05 ± 0.02 m in the horizontal direction and 0.03 ± 0.02 m in the vertical direction. Shoulder position relative to T1 was located 0.07 ± 0.02 m anteriorly, and 0.02 ± 0.04 m superiorly (0.06 and 0.00 m for males and 0.08 and 0.04 m for females, respectively). To estimate the effect of shoulder motion on trunk acceleration and L5/S1 moments, three two-dimensional dynamic link segment models were developed within the constraints of the electromagnetic tracking system and compared. Trunk segment endpoints were defined as L5/S1 and either T1 or shoulder depending on model type. For trunk accelerations, average differences between models were greater than 40 deg/s² in 70.4% trunk accelerations did not translate into significantly different moment calculations between models. Average peak dynamic L5/S1 moment differences between models were smaller than 4 Nm for all lifting conditions which failed to be statistically significant (p>0.05). The model type did not have a statistically significant effect on peak L5/S1 moments. Therefore, despite important shoulder joint translations, peak L5/S1 moments were not significantly affected.

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